58 research outputs found

    Gloss Attention for Gloss-free Sign Language Translation

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    Most sign language translation (SLT) methods to date require the use of gloss annotations to provide additional supervision information, however, the acquisition of gloss is not easy. To solve this problem, we first perform an analysis of existing models to confirm how gloss annotations make SLT easier. We find that it can provide two aspects of information for the model, 1) it can help the model implicitly learn the location of semantic boundaries in continuous sign language videos, 2) it can help the model understand the sign language video globally. We then propose \emph{gloss attention}, which enables the model to keep its attention within video segments that have the same semantics locally, just as gloss helps existing models do. Furthermore, we transfer the knowledge of sentence-to-sentence similarity from the natural language model to our gloss attention SLT network (GASLT) to help it understand sign language videos at the sentence level. Experimental results on multiple large-scale sign language datasets show that our proposed GASLT model significantly outperforms existing methods. Our code is provided in \url{https://github.com/YinAoXiong/GASLT}

    Effect of symbiotic fungi-Armillaria gallica on the yield of Gastrodia elata Bl. and insight into the response of soil microbial community

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    Armillaria members play important roles in the nutrient supply and growth modulation of Gastrodia elata Bl., and they will undergo severe competition with native soil organisms before colonization and become symbiotic with G. elata. Unraveling the response of soil microbial organisms to symbiotic fungi will open up new avenues to illustrate the biological mechanisms driving G. elata’s benefit from Armillaria. For this purpose, Armillaria strains from four main G. elata production areas in China were collected, identified, and co-planted with G. elata in Guizhou Province. The result of the phylogenetic tree indicated that the four Armillaria strains shared the shortest clade with Armillaria gallica. The yields of G. elata were compared to uncover the potential role of these A. gallica strains. Soil microbial DNA was extracted and sequenced using Illumina sequencing of 16S and ITS rRNA gene amplicons to decipher the changes of soil bacterial and fungal communities arising from A. gallica strains. The yield of G. elata symbiosis with the YN strain (A. gallica collected from Yunnan) was four times higher than that of the GZ strain (A. gallica collected from Guizhou) and nearly two times higher than that of the AH and SX strains (A. gallica collected from Shanxi and Anhui). We found that the GZ strain induced changes in the bacterial community, while the YN strain mainly caused changes in the fungal community. Similar patterns were identified in non-metric multidimensional scaling analysis, in which the GZ strain greatly separated from others in bacterial structure, while the YN strain caused significant separation from other strains in fungal structure. This current study revealed the assembly and response of the soil microbial community to A. gallica strains and suggested that exotic strains of A. gallica might be helpful in improving the yield of G. elata by inducing changes in the soil fungal community

    Reactive Oxygen Species Suppress Cardiac NaV1.5 Expression through Foxo1

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    NaV1.5 is a cardiac voltage-gated Na+ channel αsubunit and is encoded by the SCN5a gene. The activity of this channel determines cardiac depolarization and electrical conduction. Channel defects, including mutations and decrease of channel protein levels, have been linked to the development of cardiac arrhythmias. The molecular mechanisms underlying the regulation of NaV1.5 expression are largely unknown. Forkhead box O (Foxo) proteins are transcriptional factors that bind the consensus DNA sequences in their target gene promoters and regulate the expression of these genes. Comparative analysis revealed conserved DNA sequences, 5′-CAAAACA-3′ (insulin responsive element, IRE), in rat, mouse and human SCN5a promoters with the latter two containing two overlapping Foxo protein binding IREs, 5′-CAAAACAAAACA-3′. This finding led us to hypothesize that Foxo1 regulates NaV1.5 expression by directly binding the SCN5a promoter and affecting its transcriptional activity. In the present study, we determined whether Foxo1 regulates NaV1.5 expression at the transcriptional level and also defined the role of Foxo1 in hydrogen peroxide (H2O2)-mediated NaV1.5 suppression in HL-1 cardiomyocytes using chromatin immunoprecipitation (ChIP), constitutively nuclear Foxo1 expression, and RNAi Foxo1 knockdown as well as whole cell voltage-clamp recordings. ChIP with anti-Foxo1 antibody and follow-up semi-quantitative PCR with primers flanking Foxo1 binding sites in the proximal SCN5a promoter region clearly demonstrated enrichment of DNA, confirming Foxo1 recruitment to this consensus sequence. Foxo1 mutant (T24A/S319A-GFP, Foxo1-AA-GFP) was retained in nuclei, leading to a decrease of NaV1.5 expression and Na+ current, while silencing of Foxo1 expression by RNAi resulted in the augmentation of NaV1.5 expression. H2O2 significantly reduced NaV1.5 expression by promoting Foxo1 nuclear localization and this reduction was prevented by RNAi silencing Foxo1 expression. These studies indicate that Foxo1 negatively regulates NaV1.5 expression in cardiomyocytes and reactive oxygen species suppress NaV1.5 expression through Foxo1

    MIMO Radar Sparse Recovery Imaging with Wideband Interference Prediction

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    Multiple-input multiple-output (MIMO) radar three-dimensional (3D) imaging is widely applied in military and civil fields. However, MIMO is easily affected by wideband interference (WBI). To solve this problem, in this study, we propose a sparse recovery imaging method with WBI prediction based on the predictive recurrent neural network (PredRNN) and the tensor-based smooth L0 (TSL0) algorithm. Firstly, we extract the time-frequency (TF) feature of the historical measured WBI via the short-time Fourier transform (STFT) operation. In this way, we can use PredRNN to exploit the spatiotemporal correlation of the WBI in the TF domain to predict the TF feature of the WBI in the future. Then, we adaptively design the random sparse stepped frequency waveform by selecting non-overlapped frequencies with the WBI according to the predicted WBI TF feature. Finally, we apply the TSL0 algorithm to reconstruct the 3D high-resolution target image from the sparse signal cube. Simulation results show the high performance and robustness of the proposed imaging method in the presence of different WBIs

    DOA Estimation for Coprime Linear Array Based on MI-ESPRIT and Lookup Table

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    In order to improve the angle measurement performance of a coprime linear array, this paper proposes a novel direction-of-arrival (DOA) estimation algorithm for a coprime linear array based on the multiple invariance estimation of signal parameters via rotational invariance techniques (MI-ESPRIT) and a lookup table method. The proposed algorithm does not require a spatial spectrum search and uses a lookup table to solve ambiguity, which reduces the computational complexity. To fully use the subarray elements, the DOA estimation precision is higher compared with existing algorithms. Moreover, the algorithm avoids the matching error when multiple signals exist by using the relationship between the signal subspace of two subarrays. Simulation results verify the effectiveness of the proposed algorithm

    MIMO Radar Sparse Recovery Imaging with Wideband Interference Prediction

    No full text
    Multiple-input multiple-output (MIMO) radar three-dimensional (3D) imaging is widely applied in military and civil fields. However, MIMO is easily affected by wideband interference (WBI). To solve this problem, in this study, we propose a sparse recovery imaging method with WBI prediction based on the predictive recurrent neural network (PredRNN) and the tensor-based smooth L0 (TSL0) algorithm. Firstly, we extract the time-frequency (TF) feature of the historical measured WBI via the short-time Fourier transform (STFT) operation. In this way, we can use PredRNN to exploit the spatiotemporal correlation of the WBI in the TF domain to predict the TF feature of the WBI in the future. Then, we adaptively design the random sparse stepped frequency waveform by selecting non-overlapped frequencies with the WBI according to the predicted WBI TF feature. Finally, we apply the TSL0 algorithm to reconstruct the 3D high-resolution target image from the sparse signal cube. Simulation results show the high performance and robustness of the proposed imaging method in the presence of different WBIs

    Iron-Catalyzed Asymmetric Csp3–H/Csp3–H Coupling:Improve the Chirality Induction by Mechanochemical Liquid-Assisted Grinding

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    The iron-catalyzed asymmetric oxidative coupling is a challenging transformation that is typically restricted to naphthol substrates (Csp2–H) with carefully designed chiral ligands. Herein, we established a mechanochemical protocol for iron-catalyzed asymmetric Csp3–H/ Csp3–H coupling between glycines and β-ketoesters. By using size-tunable liquid additives via non-covalent bond interaction with simply designed chiral salen ligands and substrates under mechanochemical treatment, it is possible to improve the asymmetric induction and offer a variety of structurally diverse α-amino acid derivatives in high enantiopurity. Mechanistic study revealed that the iminium ion derived from acid assisted aerobic oxidation of glycine ester was the key intermediate of the reaction, and the liquid additive t-BuOH act both as a stabilizer for the iminium ion via N–H···O interaction and as an assistant for enantio-control. Moreover, a safer, cleaner, and more energy-conservation route via mechanochemical accelerated aging was first disclosed for this asymmetric Csp3–H/ Csp3–H coupling reaction
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